fix:openai return base64 image str not been recognized as base64 #647

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zerob13 merged 1 commit into ThinkInAIXYZ:dev from BowieHe:openai-image-render-error

Jul 28, 2025

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BowieHe commented Jul 28, 2025 •

edited by coderabbitai bot

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在使用OpenAI的图像生成API的时候,返回的图片不能被正确的显示
日志中debug显示为图片格式不支持

参考内部实现,发现OpenAI返回的图片对象在 b64_json 字段中,
该字段openai只会返回base64字符串, 但是不会返回前面的转义标识符
因此在后续cache的时候会被认为是不支持的格式

以防未来这个字段也会返回
data:image/png;base64

在传递到cache方法的时候加了一个判断
添加之后OpenAI图片可以被正确的识别和返回

Summary by CodeRabbit

Bug Fixes
- Improved image handling to ensure all generated images are correctly formatted and display reliably, regardless of their original format.


          fix:openai return base64 image str not been recognized as base64

8524bb7

Contributor

coderabbitai bot commented Jul 28, 2025 •

edited

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Walkthrough

The changes update the handling of base64-encoded image data returned by the OpenAI image generation API. Both affected modules now ensure that base64 strings are consistently prefixed with "data:image/png;base64," before caching, guaranteeing proper data URI formatting for PNG images.

Changes

Cohort / File(s)	Change Summary
OpenAI-Compatible Provider base64 Handling `src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts`	Modified to check and prepend "data:image/png;base64," to base64 image data before caching.
OpenAI Responses Provider base64 Handling `src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts`	Updated to verify and prepend "data:image/png;base64," to base64 image data in the JSON response.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~7 minutes

Poem

A bunny hopped through code so neat,
Ensuring image strings are sweet—
With prefixes for PNG,
The cache now sings in harmony.
Base64 wrapped up just right,
Data URIs now take flight!
🐇✨

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📒 Files selected for processing (2)

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts (1 hunks)
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts (1 hunks)

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**/*.{ts,tsx,js,jsx,vue}

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Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

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Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

src/main/**/*.ts

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Use Electron's built-in APIs for file system and native dialogs

Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

src/main/presenter/**/*.ts

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One presenter per functional domain

Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

src/main/presenter/llmProviderPresenter/providers/*.ts

📄 CodeRabbit Inference Engine (CLAUDE.md)

src/main/presenter/llmProviderPresenter/providers/*.ts: Create provider file in src/main/presenter/llmProviderPresenter/providers/ when adding a new LLM provider
Implement coreStream method following standardized event interface in LLM provider files

src/main/presenter/llmProviderPresenter/providers/*.ts: Each file in src/main/presenter/llmProviderPresenter/providers/*.ts should handle interaction with a specific LLM API, including request/response formatting, tool definition conversion, native/non-native tool call management, and standardizing output streams to a common event format.
Provider implementations must use a coreStream method that yields standardized stream events to decouple the main loop from provider-specific details.
The coreStream method in each Provider must perform a single streaming API request per conversation round and must not contain multi-round tool call loop logic.
Provider files should implement helper methods such as formatMessages, convertToProviderTools, parseFunctionCalls, and prepareFunctionCallPrompt as needed for provider-specific logic.
All provider implementations must parse provider-specific data chunks and yield standardized events for text, reasoning, tool calls, usage, errors, stop reasons, and image data.
When a provider does not support native function calling, it must prepare messages using prompt wrapping (e.g., prepareFunctionCallPrompt) before making the API call.
When a provider supports native function calling, MCP tools must be converted to the provider's format (e.g., using convertToProviderTools) and included in the API request.
Provider implementations should aggregate and yield usage events as part of the standardized stream.
Provider implementations should yield image data events in the standardized format when applicable.
Provider implementations should yield reasoning events in the standardized format when applicable.
Provider implementations should yield tool call events (`tool_call_star...

Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

**/*.{js,jsx,ts,tsx}

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Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

src/{main,renderer}/**/*.ts

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src/{main,renderer}/**/*.ts: Use context isolation for improved security
Implement proper inter-process communication (IPC) patterns
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Implement proper error handling and logging for debugging

Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

src/main/**/*.{ts,js,tsx,jsx}

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Files:

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts
src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts

🧠 Learnings (2)

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts (10)

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield image data events in the standardized format when applicable.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : All provider implementations must parse provider-specific data chunks and yield standardized events for text, reasoning, tool calls, usage, errors, stop reasons, and image data.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Each file in src/main/presenter/llmProviderPresenter/providers/*.ts should handle interaction with a specific LLM API, including request/response formatting, tool definition conversion, native/non-native tool call management, and standardizing output streams to a common event format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : When a provider supports native function calling, MCP tools must be converted to the provider's format (e.g., using convertToProviderTools) and included in the API request.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider files should implement helper methods such as formatMessages, convertToProviderTools, parseFunctionCalls, and prepareFunctionCallPrompt as needed for provider-specific logic.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/providers.ts : Add provider configuration in configPresenter/providers.ts when adding a new LLM provider

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : When a provider does not support native function calling, it must prepare messages using prompt wrapping (e.g., prepareFunctionCallPrompt) before making the API call.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations must use a coreStream method that yields standardized stream events to decouple the main loop from provider-specific details.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Implement coreStream method following standardized event interface in LLM provider files

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield tool call events (tool_call_start, tool_call_chunk, tool_call_end) in the standardized format.

src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts (10)

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield image data events in the standardized format when applicable.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : All provider implementations must parse provider-specific data chunks and yield standardized events for text, reasoning, tool calls, usage, errors, stop reasons, and image data.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Each file in src/main/presenter/llmProviderPresenter/providers/*.ts should handle interaction with a specific LLM API, including request/response formatting, tool definition conversion, native/non-native tool call management, and standardizing output streams to a common event format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : When a provider supports native function calling, MCP tools must be converted to the provider's format (e.g., using convertToProviderTools) and included in the API request.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/providers.ts : Add provider configuration in configPresenter/providers.ts when adding a new LLM provider

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider files should implement helper methods such as formatMessages, convertToProviderTools, parseFunctionCalls, and prepareFunctionCallPrompt as needed for provider-specific logic.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Implement coreStream method following standardized event interface in LLM provider files

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : When a provider does not support native function calling, it must prepare messages using prompt wrapping (e.g., prepareFunctionCallPrompt) before making the API call.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield text events in the standardized format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations must use a coreStream method that yields standardized stream events to decouple the main loop from provider-specific details.

🔇 Additional comments (2)

src/main/presenter/llmProviderPresenter/providers/openAIResponsesProvider.ts (1)

441-445: LGTM! Proper handling of OpenAI base64 image data format.

The conditional check correctly ensures base64 data is formatted as a proper data URI before caching. This addresses the issue where OpenAI's b64_json field may or may not include the data:image/png;base64, prefix, preventing caching failures due to unsupported format detection.

src/main/presenter/llmProviderPresenter/providers/openAICompatibleProvider.ts (1)

417-421: LGTM! Consistent base64 image data handling across providers.

The implementation mirrors the fix in openAIResponsesProvider.ts, ensuring consistent handling of OpenAI's base64 image data across different provider implementations. This maintains uniform behavior and prevents caching issues regardless of which OpenAI provider is used.

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Collaborator

zerob13 commented Jul 28, 2025

LGTM

zerob13 merged commit e4a8933 into ThinkInAIXYZ:dev

2 checks passed

coderabbitai bot mentioned this pull request

feat: support openrouter gemini 2.5 flash image preview #791

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coderabbitai bot mentioned this pull request

refactor: translate all cn comments and log to en #871

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